AI/ML Research Engineer

🏢 Manifoldbio · 📍 Boston, MA or San Francisco, CA 💰 $140,000 - $140,000 / yr

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Position Summary & Responsibilities

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively multiplexed in vivo screening to unlock tissue-targeted medicines and organism-scale models of living systems. Using proprietary molecular barcoding technology, we screen hundreds of thousands of protein designs simultaneously in living systems, producing in vivo-validated datasets at a scale no one else can match. The datasets power our computational models, which leads to better drug designs, creating a flywheel that gets stronger with every campaign. Our team of protein engineers, biologists, and computational scientists works across this full stack to pursue programs both internally and with leading pharma companies.

Position

Manifold Bio is seeking a talented Machine Learning Research Engineer to join our growing AI team. You will work closely with our research scientists to implement, scale, and optimize machine learning systems that power our de novo antibody design platform and advance our protein design capabilities. Your efforts will contribute to building production-ready ML infrastructure that enables breakthrough discoveries in protein therapeutics. You will be expected to take ownership of engineering challenges in our ML pipeline, from data processing and model training to deployment and monitoring, while collaborating closely with our research team to translate cutting-edge ideas into robust, scalable systems.

This is an on-site role and can be based in either Boston, Massachusetts or San Francisco, California. Please only apply if you reside in these cities or are open to relocate.

Responsibilities

Implement and optimize machine learning models for protein design
Build and maintain scalable data processing pipelines for large-scale protein and molecular datasets
Develop and deploy ML infrastructure for distributed training and inference across GPU clusters
Collaborate with research scientists to translate experimental ML approaches into production-ready code
Design and execute ML experiments with clear hypotheses and rigorous analysis
Optimize model performance and computational efficiency for large-scale protein design tasks<

🎯 Candidate Preparation Guide For Manifoldbio Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Scientific rigor combined with high-velocity engineering is tested intensely; interviewers look for pioneers who can build multiplexed protein measurement platforms at scale.

📋 Preparation Priorities (Key Areas to Clarify):

1. Working strictly in academic silos without an appreciation for commercial drug discovery timelines
2. Inability to troubleshoot unexpected assay failures with data-driven pragmatism
3. Resistance to cross-disciplinary collaboration between wet-lab scientists and computational teams

✨ Recommended Role Alignment Hook:

I build high-throughput protein measurement engines that accelerate therapeutic discovery by turning complex biological data into actionable insights.

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